651 to 675 of 964 PyTorch Jobs

statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows. Visualization & Communication: Ability to create More ❯

data modeling Containers: Docker; orchestration tools Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you More ❯

data modeling Containers: Docker; orchestration tools Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you More ❯

data modeling Containers: Docker; orchestration tools Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you More ❯

data modeling Containers: Docker; orchestration tools Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you More ❯

data modeling Containers: Docker; orchestration tools Infra as Code: Terraform, CloudFormation Monitoring: Prometheus, Grafana, ELK Security & Compliance: Data protection and access control Nice-to-Haves AI/ML integration (PyTorch, HF etc.) MLOps (MLflow, Kubeflow, SageMaker) Vector search (Pinecone, pgvector, Weaviate, Qdrant etc.) Video ingestion pipelines & codecs 💡Don’t worry if you haven’t used these exact tools. If you More ❯

with a strong interest and practical experience in applied AI or machine learning. Strong programming skills in Python (or similar languages) with familiarity in AI/ML libraries (TensorFlow, PyTorch, etc.). Experience working with large-scale models (LLM/VLM) and deploying AI-driven solutions into production. Solid understanding of cloud technologies, containerization, and building scalable AI applications. Ability More ❯

consultancy, or fast-paced business. Strong programming skills in Python, with experience building automation workflows, APIs, and data pipelines. Exposure to AI/ML frameworks (e.g. OpenAI, LangChain, TensorFlow, PyTorch). Solid knowledge of SQL and data warehousing concepts. Demonstrated experience with cloud platforms ( GCP & Azure preferred). Strong understanding of data modelling, transformation, and orchestration (e.g. dbt, Airflow, Azure More ❯

time ML applications Maintain and improve recommender systems Build and work with modern API and microservices architectures Qualifications Strong foundation in Python Experience with machine learning, familiar with Huggingface, Pytorch, and similar ML tools and packages Familiarity with deploying and scaling ML models in the cloud, particularly with AWS and SageMaker Understanding of DevOps processes and tools: CI/CD More ❯

consultancy, or fast-paced business. Strong programming skills in Python, with experience building automation workflows, APIs, and data pipelines. Exposure to AI/ML frameworks (e.g. OpenAI, LangChain, TensorFlow, PyTorch). Solid knowledge of SQL and data warehousing concepts. Demonstrated experience with cloud platforms ( GCP & Azure preferred). Strong understanding of data modelling, transformation, and orchestration (e.g. dbt, Airflow, Azure More ❯

consultancy, or fast-paced business. Strong programming skills in Python, with experience building automation workflows, APIs, and data pipelines. Exposure to AI/ML frameworks (e.g. OpenAI, LangChain, TensorFlow, PyTorch). Solid knowledge of SQL and data warehousing concepts. Demonstrated experience with cloud platforms ( GCP & Azure preferred). Strong understanding of data modelling, transformation, and orchestration (e.g. dbt, Airflow, Azure More ❯

documents and work with native Japanese speakers Technical proficiency You write production-grade, scalable Python code, ensuring that your models are robust, maintainable, and optimised for performance. Comfortable with PyTorch Knowledge of Transformer-based models Knowledge of Large Language Models (LLMs) Proven experience of having delivered successful either Computer Vision or LLM projects into production Strong understanding of software development More ❯

practical experience. 7 years of experience working in AI/ML as a technical sales engineer or in software engineering. Experience in Python and Machine learning frameworks (e.g., TensorFlow, PyTorch). Experience in Generative AI as a user or a developer. Experience delivering technical presentations and leading business value sessions to support client relationship management in this region. Preferred qualifications More ❯

consultancy, or fast-paced business. Strong programming skills in Python, with experience building automation workflows, APIs, and data pipelines. Exposure to AI/ML frameworks (e.g. OpenAI, LangChain, TensorFlow, PyTorch). Solid knowledge of SQL and data warehousing concepts. Demonstrated experience with cloud platforms ( GCP & Azure preferred). Strong understanding of data modelling, transformation, and orchestration (e.g. dbt, Airflow, Azure More ❯

consultancy, or fast-paced business. Strong programming skills in Python, with experience building automation workflows, APIs, and data pipelines. Exposure to AI/ML frameworks (e.g. OpenAI, LangChain, TensorFlow, PyTorch). Solid knowledge of SQL and data warehousing concepts. Demonstrated experience with cloud platforms ( GCP & Azure preferred). Strong understanding of data modelling, transformation, and orchestration (e.g. dbt, Airflow, Azure More ❯

AI models, preferably within high-performance or real-time environments. Proficiency in programming languages such as Python, R, or Java. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of data analysis, statistical methods, and predictive modelling. Excellent problem-solving skills and attention to detail. Effective communication and collaboration abilities. Preferred Skills (desirable but More ❯

AI models, preferably within high-performance or real-time environments. Proficiency in programming languages such as Python, R, or Java. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of data analysis, statistical methods, and predictive modelling. Excellent problem-solving skills and attention to detail. Effective communication and collaboration abilities. Preferred Skills (desirable but More ❯

Proficiency in Python and SQL and familiarity with good software engineering practices Excellent written and verbal communication Strong experience developing, testing machine learning solutions using frameworks such as TensorFlow, PyTorch or scikit-learn Solid intuitive grasp of fundamental concepts from probability, statistics, linear algebra and calculus Collaborative, humble and enthusiastic attitude Preferred qualifications, capabilities and skills Experience deploying on AWS More ❯

record of high-quality research, evidenced by publications in reputable scientific journals or conferences. Expertise in software development and programming in Python. Experience with deep learning frameworks such as PyTorch, JAX, and/or TensorFlow. Excellent ability to communicate complex ideas clearly, both verbally and in writing, and to work effectively within a multidisciplinary team. Strong analytical and critical thinking More ❯

hurdles. Ability to translate business questions into analytical frameworks and interpret results for non-technical stakeholders. Strong proficiency in Python, SQL, and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Experience with model operationalization using tools like Docker, Kubernetes, MLflow, or SageMaker. Marketing KPIs knowledge: CTR, conversion rate, MQL to SQL, ROI, CLV, CAC, retention. Experience working with multi … or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with cloud data warehouses (e.g., Snowflake, Databricks, Redshift More ❯

hurdles. Ability to translate business questions into analytical frameworks and interpret results for non-technical stakeholders. Strong proficiency in Python, SQL, and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Experience with model operationalization using tools like Docker, Kubernetes, MLflow, or SageMaker. Marketing KPIs knowledge: CTR, conversion rate, MQL to SQL, ROI, CLV, CAC, retention. Experience working with multi … or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with cloud data warehouses (e.g., Snowflake, Databricks, Redshift More ❯

hurdles. Ability to translate business questions into analytical frameworks and interpret results for non-technical stakeholders. Strong proficiency in Python, SQL, and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Experience with model operationalization using tools like Docker, Kubernetes, MLflow, or SageMaker. Marketing KPIs knowledge: CTR, conversion rate, MQL to SQL, ROI, CLV, CAC, retention. Experience working with multi … or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with cloud data warehouses (e.g., Snowflake, Databricks, Redshift More ❯

experience in ML/AI (LLMs, recommender systems, data mining, or similar). Proven hands-on work with LLM agents/generative AI . Strong coding in Python with PyTorch/TensorFlow . Advanced debugging, experimentation, and optimisation skills. Master's or PhD in Computer Science, AI, ML, or related field . Bonus Skills: Research background (papers, Kaggle Master). More ❯

major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and DL models using tools like Axolotl, LoRA, or QLoRA. More ❯

major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and DL models using tools like Axolotl, LoRA, or QLoRA. More ❯